DOMESTIC AND FOREIGN SOURCE SHOCKS TO THE INDONESIAN STOCK MARKET: TIME SERIES EVIDENCE. Bhayu Purnomo Georgia State University

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1 DOMESTIC AND FOREIGN SOURCE SHOCKS TO THE INDONESIAN STOCK MARKET: TIME SERIES EVIDENCE Bhayu Purnomo Georgia State University

2 Purpose 1. Understand the effect of domestic and foreign source shocks to the Indonesian stock market. 2. Create a well defined economic surveillance strategy.

3 Motivation Capital market development plays an important role in economic growth of emerging economies. One of the channels of capital movements is through stock markets. The adverse volatility effects of hot money can be substantial for emerging economies, for example the Asian financial crisis in 1997.

4 1997 Asia financial crisis: regional exchange rates and stock market indexes Index Jan 1995 = Singapore Dollar Malaysian Ringgit Thailand Bath Index January 1995 = Indonesia JCI Index US S&P 500 Index Singapore FSSTI Index 0.2 Indonesian IDR 50 Thailand SET Index Japan NKY Index

5 1997 Asian financial crisis: Indonesia US $ Million Jan 96 Jan 97 Jan 98 Jan 99 Jan 00 Jan 01 Jan 02 Jan % 30.00% 20.00% 10.00% 0.00% 10.00% Capital Account Electricity Consumption Growth (RHS) GDP Growth (RHS) Source : Indonesian Ministry of Finance 20.00% 30.00%

6 Literature review Corsetti et al.(1999): Contagion created by sudden shifts in market expectations and confidence. Cerra and Saxena (2000): 1998 Indonesian economic crisis was a clear case of contagion. Tambunan (2010): Integration into world markets is creating vulnerabilities for the Indonesian economy.

7 Hypothesis Two sources of shocks (Monthly data ): 1. Domestic macroeconomic variables: Money supply, Exchange rate, and Industrial production. 2. Foreign source shocks: Regional stock markets: Malaysia, Thailand, Singapore, Philippines Advanced country stock markets: Japan & US

8 Model specification depends on degree of integration Variables (in natural log form) Augmented Dickey Fuller Test Phillip Perron Test t statistic inference* Adj t statistic inference* Domestic Macroeconomic Variable Money Supply 0.42 Nonstationary 1.65 Nonstationary Industrial Production 0.07 Nonstationary 4.34 Stationary Exchange Rate 4.49 Stationary 4.24 Stationary Stock Market Indexes Indonesian Stock Market Index 0.06 Nonstationary 0.02 Nonstationary Singapore Stock Index 2.08 Nonstationary 1.88 Nonstationary Malaysian Stock Index 1.91 Nonstationary 1.56 Nonstationary Thailand Stock Index 1.38 Nonstationary 1.45 Nonstationary Phillipines Stock Index 1.19 Nonstationary 1.14 Nonstationary Japan Stock Index 1.63 Nonstationary 1.69 Nonstationary S&P 500 Stock Index 2.93 Nonstationary 2.80 Nonstationary * Tested at 1% level

9 Econometric strategy Autoregressive distributed lag framework is used to examine the long-run relationship between the variables. ARDL is applicable whether the underlying variables are I(0), I(1), or fractionally integrated. Error Correction Model is estimated to find the short-run relationship between the variables.

10 ARDL model Δln 0 Δln Δln2 Δln Δln Δln 0 0 Δln Δln 0 0 Δln Δln Δln ln 1 2 ln2 1 3 ln 1 4 ln 1 5 ln 1 6 ln 1 7 ln 1 8 ln 1 9 ln 1 10 ln 1

11 Regression results The Wald test statistic lies above the upper bound of the critical value, suggesting there is a long-run relationship between the variables. The null hypothesis of no cointegration (no long-run relationship) 0. tested against 0. Test Statistic Max Lag Significance Bound Critical Values Level unrestricted intercept and no trend* Lower Bound Upper Bound 1% % % * Taken from Pesaran (2001)

12 Error correction model Independent Variables Dependent Variable : F Statistic P value Domestic Macroeconomic Variable Money Supply Industrial Production 2.17* Exchange Rate 3.09* Stock Market Indexes Malaysian Stock Index 3.18* Singapore Stock Index 3.57* Phillipines Stock Index 10.2* Thailand Stock Index 3.70* Japan Stock Index 5.28* S&P 500 Stock Index ECM Coefficient (t statistic)* 0.90 (0.000) Diagnostic Test Ho : No serial correlation Ho : No Heteroskedasticity Ho: Residuals are normally distributed R Square 0.84 * Statistically significant at 5% level

13 Results of Granger causality tests Dependent Variable Independent Variable Relation Granger Causality Indonesian Stock Market Index Exchange Rate Significant Evident Industrial Production Significant Evident Money Supply Not Significant Not Evident Exchange Rate Industrial Production Not Significant Not Evident Money Supply Significant Evident Indonesian Stock Market Index Significant Industrial Production Money Supply Not Significant Not Evident Indonesian Stock Market Index Significant Exchange Rate Significant Money Supply Indonesian Stock Market Index Significant Exchange Rate Significant Industrial Production Not Significant

14 Impulse Response Function Response of Indonesian Stock Market Index to a shock in Response Singapore of Stock LJCI to Market LFSSTI Index Response of Indonesian Stock Market Index to a shock Response in Indonesian of LJCI Money to LIP Supply % of change Response of Indonesian Stock Market Index to a shock in Response Jappanese of Stock LJCI to Market LNKY Index Response of Indonesian Stock Market Index to a shock Response in USD IDR of Exchange LJCI to LER Rate Month Month

15 Conclusions for economic surveillance Industrial production and the dollar exchange rate appear to be important predictors of future movements in the Indonesian stock market. Money supply is a less substantial predictor of future movements in the Indonesian stock market. Policy makers and investors in Indonesia should monitor regional stock markets.

16 Conclusion The exchange rate has a substantial indirect effect on the level of macroeconomic activity where the stock market is the mediating variable. The US stock market may have an indirect effect on Indonesia s economy and that influence may be transmitted through other pathways than those examined here.

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